Confidence Regions for Multivariate Calibration: a proposal

Most of the papers on calibration are based on either classic or bayesian parametric context. In addition to the typical problems of the parametric approach (choice of the distribution for the measurement errors, choice of the model that links the sets of variables, etc.), a relevant problem in calibration is the construction of confidence region for the unknown levels of the explanatory variables. In this paper we propose a semiparametric approach, based on simplicia1 depth, to test the hypothesis of linearity of the link function and then how to find calibration depth confidence regions.